Present-day semiconductor wafer fabrication factories (or ‘fabs’) are extremely complex environments that require an extraordinary amount of coordination. A typical fab may consist of hundreds of wafer processing functional units. Examples of these functional units include modules, submodules, tools, cluster tools, chambers, and any other entities responsible for performing one or more of a variety of operations or processes on a semiconductor wafer. The subject of processing by these functional units includes semiconductor wafers, which may be processed into a wide variety of items such as logic (e.g., central processing units) or memory (e.g., DRAMs). Each tool in the fab is responsible for performing one or more operations or series of operations that result in the final product. After a tool performs its operation, the wafer may be forwarded to a downstream tool where additional operations or series of operations may be performed. Each tool may process wafers according to hundreds of distinct processes, with each having hundreds of individual steps. Ultimately, the sum of the operations performed by these tools (e.g., the functional units in the fab) on the wafer results in the final product or the final state of the wafer.
In typical situations, the tools may be grouped, either logically or physically, into modules (which constitute a higher level functional unit relative to the tools) to produce a module level product (e.g., a product at the module level). For example, a number of tools may be grouped together in a copper wiring module to produce intricate copper geometric circuit patterns on the substrate of a wafer. These modules may include, at one or more portions thereof, any number of tools such as, for example, electro chemical plating (ECP) tools, chemical mechanical polishing (CMP) tools, and other similar tools. In a typical processing scheme, wafers are initially moved into a chamber of the ECP tool where an electroplating or plating process takes place. The result of the plating process is the application of, for example, a thin layer of copper on the wafer substrate. From there, the wafer may be moved downstream to a CMP tool. The CMP tool polishes the wafer to remove any excess metallization (i.e., the plating or plated material). Afterwards, the wafer may be moved to the next tool in the module, which may include, for example, a barrier polishing or other similar tool. The end result or final product of the module includes the remaining copper material, which forms the desired copper geometric circuit pattern.
In addition to the above-described processes performed by the functional units on a wafer (e.g., the application and subsequent polishing of metallization by tools in a copper wiring module), a number of quality control operations may be implemented within the functional units to improve the overall quality of the fab. In typical situations, any number of wafer attributes or properties may be measured during or after processing by a functional unit. These measured properties may then be compared against the expected results or target parameters. If a measured property deviates too greatly from an expected result, a modification or adjustment may be made to the processing operation or procedure of the functional unit in an attempt to address the deficiency.
Thus, with the copper wiring module described above, after plating by an ECP tool, the thickness of a layer applied to a wafer may be measured to generate a thickness profile. If the plated layer is too thick, the ECP tool recipe may be modified to decrease a plating time (i.e., the amount of time plating material is applied to the wafer). In a similar manner, after polishing at a CMP tool, the thickness of the polished layer may be similarly measured. If the layer is too thick, the CMP tool recipe may be modified to increase a polishing time (i.e., the amount of time the wafer is polished). In this manner, the control processes of the individual functional units within a fab may be modified to increase effectiveness and efficiency.
To implement these quality control measures, conventional wafer manufacturing systems contemplate, for example, that an engineer may inspect the product of a process after each step and manually update the recipe of that particular functional unit to address any unsatisfactory results. These products are monitored by using, for example, sensors or metrology devices after each processing step. More particularly, a wafer may be physically removed from the processing line, where any number of wafer properties may be measured, and subsequently returned to the line. For example, in the copper wiring module described above, a wafer may be removed after processing from a chamber in an ECP tool to allow measuring of a copper thickness. From there, the measured properties (e.g., the copper thickness) may be compared against the expected results or target parameters. When a less than satisfactory property or condition is identified, a modification may be made to the functional unit recipe to address the deficiency.
While these techniques addressed some of the problems faced with certain types of individual functional units (e.g., situations where the results of processing by a lone tool have drifted outside an acceptable range), they failed to consider the dramatic impact a wafer property at one functional unit could have on the processing effectiveness of another functional unit. Instead of sharing information between the functional units (e.g., between the ECP and CMP tools of a copper wiring module), the conventional approach was to address each functional unit and each problem individually.
One reason for this approach was the limited connectivity capability of the functional units. For example, the ECP tools and CMP tools of a copper wiring module were not capable of communicating easily with each other. Other reasons stemmed from the inability of the metrology devices of those functional units to collect data at a wafer level basis.
As a result, these conventional quality control processes had no way of addressing a deficient property measured at one functional unit anywhere but at that functional unit. Similarly, these processes did not share or transfer information upstream, downstream, or between runs to optimize processing. Thus, information measured at a CMP tool was not fed back to an ECP tool for purposes of optimizing processing of the CMP tool. This led to situations where one deficiency or problem may have been compounded by the existence of other problems at other functional units. In some cases, the remedies to a problem at one functional unit produced a result that may have been satisfactory to the first functional unit, but resulted in a condition or deficiency that was impossible to resolve at a downstream functional unit. As an example, to address the problem of a thicker than desirable plated layer, an ECP tool might decrease a plating time. While this modification may have resulted in a satisfactory result at the ECP tool, it may have also left a layer so thin that downstream CMP tools could not adequately process the wafer.
In the above and other cases, processing at one functional unit may be more effective if information could be utilized at other functional units to produce results that increase the effectiveness of processing of the first functional unit. For example, a CMP tool may process wafers more effectively if it could forward optimal processing information to an ECP tool. In this manner, the CMP tool may instruct the ECP tool to, for example, decrease a plating thickness.
What is therefore needed is a technique for optimizing semiconductor wafer manufacturing processes within a copper wiring module. Specifically, what is needed is a technique that transfers information from one tool within the copper wiring module to another for purpose of optimizing a copper wiring module output property. What is also needed is a technique that allows information or data to be transmitted between copper wiring module tools and/or processing runs. As a result, a tool may direct or request another tool to produce a result that provides optimal processing conditions for the requesting tool.